{"id":"https://openalex.org/W3089044119","doi":"https://doi.org/10.1109/mis.2020.3026715","title":"MDA: Multimodal Data Augmentation Framework for Boosting Performance on Sentiment/Emotion Classification Tasks","display_name":"MDA: Multimodal Data Augmentation Framework for Boosting Performance on Sentiment/Emotion Classification Tasks","publication_year":2020,"publication_date":"2020-09-25","ids":{"openalex":"https://openalex.org/W3089044119","doi":"https://doi.org/10.1109/mis.2020.3026715","mag":"3089044119"},"language":"en","primary_location":{"id":"doi:10.1109/mis.2020.3026715","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mis.2020.3026715","pdf_url":null,"source":{"id":"https://openalex.org/S114241109","display_name":"IEEE Intelligent Systems","issn_l":"1541-1672","issn":["1541-1672","1941-1294"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101687663","display_name":"Nan Xu","orcid":"https://orcid.org/0000-0002-9794-7262"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nan Xu","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035983004","display_name":"Wenji Mao","orcid":"https://orcid.org/0000-0003-2323-5091"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenji Mao","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059038918","display_name":"Penghui Wei","orcid":"https://orcid.org/0000-0002-8701-9833"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Penghui Wei","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038521974","display_name":"Daniel Zeng","orcid":"https://orcid.org/0000-0002-9046-222X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Daniel Zeng","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101687663"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":1.7809,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.88206523,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"36","issue":"6","first_page":"3","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8398513793945312},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.7189675569534302},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5943641066551208},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5146576166152954},{"id":"https://openalex.org/keywords/multimodal-learning","display_name":"Multimodal learning","score":0.45840388536453247},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.44992363452911377},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.437398225069046},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32638633251190186}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8398513793945312},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7189675569534302},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5943641066551208},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5146576166152954},{"id":"https://openalex.org/C2780660688","wikidata":"https://www.wikidata.org/wiki/Q25052564","display_name":"Multimodal learning","level":2,"score":0.45840388536453247},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.44992363452911377},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.437398225069046},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32638633251190186},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mis.2020.3026715","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mis.2020.3026715","pdf_url":null,"source":{"id":"https://openalex.org/S114241109","display_name":"IEEE Intelligent Systems","issn_l":"1541-1672","issn":["1541-1672","1941-1294"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6499775606","display_name":null,"funder_award_id":"11832001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G997903294","display_name":null,"funder_award_id":"71621002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W4919037","https://openalex.org/W2075456404","https://openalex.org/W2122838776","https://openalex.org/W2250243742","https://openalex.org/W2253866532","https://openalex.org/W2265228180","https://openalex.org/W2585635281","https://openalex.org/W2591340154","https://openalex.org/W2763922629","https://openalex.org/W2798802604","https://openalex.org/W2894786240","https://openalex.org/W2896480997","https://openalex.org/W2916132663","https://openalex.org/W2922352340","https://openalex.org/W2955221632","https://openalex.org/W2963449390","https://openalex.org/W2963456134","https://openalex.org/W2964010806","https://openalex.org/W2965096309","https://openalex.org/W2971296908","https://openalex.org/W4295727797","https://openalex.org/W6600213771","https://openalex.org/W6692145052","https://openalex.org/W6751795773"],"related_works":["https://openalex.org/W2003125512","https://openalex.org/W3192794374","https://openalex.org/W4362613237","https://openalex.org/W4313488044","https://openalex.org/W1996541855","https://openalex.org/W1987859285","https://openalex.org/W3195168932","https://openalex.org/W2543725295","https://openalex.org/W2897195263","https://openalex.org/W2340694410"],"abstract_inverted_index":{"Multimodal":[0,83],"data":[1,17,39,58],"analysis":[2,18,131,135],"has":[3],"drawn":[4],"increasing":[5],"attention":[6],"with":[7],"the":[8,33,73,89,112,122,128,137,141,145,152],"explosive":[9],"growth":[10],"of":[11,37,76,124,147],"multimedia":[12],"data.":[13,52,67],"Although":[14],"traditional":[15],"unimodal":[16,48,109],"tasks":[19,139],"have":[20],"accumulated":[21],"abundant":[22],"labeled":[23,28,77],"datasets,":[24],"there":[25,54],"are":[26],"few":[27],"multimodal":[29,38,51,62,78,92,113,129,133,155],"datasets":[30,110],"due":[31],"to":[32,45,50,71,103,120],"difficulty":[34],"and":[35,116,132,140],"complexity":[36],"annotation,":[40],"nor":[41],"is":[42,55],"it":[43],"easy":[44],"directly":[46],"transfer":[47],"knowledge":[49],"Unfortunately,":[53],"little":[56],"related":[57],"augmentation":[59],"work":[60],"in":[61],"domain,":[63],"especially":[64],"for":[65,87,150],"image\u2013text":[66,93,105],"In":[68],"this":[69,118],"article,":[70],"address":[72],"scarcity":[74],"problem":[75],"data,":[79],"we":[80],"propose":[81],"a":[82,99],"Data":[84],"Augmentation":[85],"framework":[86,97,149],"boosting":[88,151],"performance":[90,123,153],"on":[91,154],"classification":[94,156],"task.":[95,157],"Our":[96],"learns":[98],"cross-modality":[100],"matching":[101],"network":[102],"select":[104],"pairs":[106],"from":[107],"existing":[108],"as":[111,136],"synthetic":[114],"dataset,":[115],"uses":[117],"dataset":[119],"enhance":[121],"classifiers.":[125],"We":[126],"take":[127],"sentiment":[130],"emotion":[134],"experimental":[138,142],"results":[143],"show":[144],"effectiveness":[146],"our":[148]},"counts_by_year":[{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}